AI RESEARCH
CRFT: Consistent-Recurrent Feature Flow Transformer for Cross-Modal Image Registration
arXiv CS.AI
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ArXi:2604.05689v1 Announce Type: cross We present Consistent-Recurrent Feature Flow Transformer (CRFT), a unified coarse-to-fine framework based on feature flow learning for robust cross-modal image registration. CRFT learns a modality-independent feature flow representation within a transformer-based architecture that jointly performs feature alignment and flow estimation. The coarse stage establishes global correspondences through multi-scale feature correlation, while the fine stage refines local details via hierarchical feature fusion and adaptive spatial reasoning.